Methods of spatial analysis will be used to explain observed geographic patterns of human variation (blood groups, electrophoretic mutants, anthropometric variables). These will be studied on geographic scales ranging from continents to clusters of villages in an attempt to isolate and identify components due to selection, migration, and to genetic drift by combined consideration of geographic variation patterns and spatial correlograms. Patterns of selection will result in geographic variation patterns with corresponding spatial correlograms for a few variables at a time; migration will result in similar variation patterns and correlograms for most variables examined; whereas genetic drift will result in different geographic variation patterns but identical correlograms for different variables. We propose to substantiate that stochastic gene frequency distributions near stationarity have identical correlograms; and to ascertain the rate at which correlograms of stochastic spatial processes with identical generating functions converge as well as the magnitude of differences in parameters of these processes detectable by means of correlograms. Thus a test of significance for the null hypothesis of parallelism among correlograms is necessary and will be developed by a Monte Carlo approach. This will be done using an available simulation program for isolation-by-distance with or without modification by selection. The human data to be analyzed are gene frequencies and morphometric data of European, Asian and African populations and several selected sets on a smaller geographic scale. We plan to compare different methods of spatial analysis and their abilities for resolving spatial patterns and of identifying underlying processes. The Mantel test, spatial autocorrelation analysis, kriging, empirical orthogonal functions, and Fourier analysis will be studied in this manner. For these tests we plan to create a second simulation model in which populations are the basic units and in which processes of selection, migration and drift can be simulated on areas with specific physiographic and topographic properties.